Anthropic and OpenAI in figures ahead of IPO

Roman Z., venture analyst at Raison

The history of OpenAI and Anthropic is reminiscent of the film “Ford v Ferrari.” One company makes a cheaper, more mass-market product, while the other wins on quality and costs more, and at different points in the race, first one and then the other pulls ahead. Both are now preparing for IPOs. Anthropic has postponed its listing to November, while OpenAI has targeted 2027. It is a good time to take stock of where each stands.

How it all began

OpenAI appeared in 2015 as a nonprofit organization whose goal was to create AGI (Artificial General Intelligence) safely and in a way that would benefit all humanity. But AI development requires enormous amounts of money, and donations alone are not enough. Gradually, the company moved to a commercial model.

In 2021, part of the team led by Dario Amodei, who headed research at OpenAI, left and founded Anthropic. One of the main disagreements was alignment — the task of ensuring that AI follows not only the wording of a prompt, but also its meaning. For example, if you ask a model to hold users’ attention, it may start using clickbait. Formally, the goal is achieved, but not as intended.

The more powerful the model, the more serious the consequences of such errors, and Anthropic’s founders believed that OpenAI was paying too little attention to this issue. Since then, safety in development has remained an important part of Anthropic’s identity, although its approach also draws criticism in the industry.

Where the $25 billion revenue gap comes from

Over several years, both companies have grown from research labs into the world’s largest private AI businesses, and the difference between them is best seen in revenue. For comparison, we use ARR (annualized revenue run rate) — revenue for the latest month or quarter, annualized.

• Anthropic — $65 billion, according to CNBC
• OpenAI — more than $40 billion, according to Bloomberg

The gap is explained by a combination of two factors:

1. Anthropic has a stronger presence in the enterprise segment, where the most money is
2. Its tokens are more expensive, and its models consume more of them.

Even if both companies’ systems were used to solve the same tasks in the same volume, Anthropic would earn more from them. Token pricing and usage are compared by Artificial Analysis.

Valuation and multiples

To compare valuations, we use the P/S (price-to-sales) multiple. It shows how many times a company’s valuation exceeds its annual revenue. It is usually calculated using actual revenue, but Anthropic and OpenAI do not publish financial statements, so we use ARR.

There is a nuance to this approach. Both companies are growing quickly, so ARR is higher than their average revenue over the past year, which makes the multiple lower and the companies look slightly cheaper. But for Anthropic and OpenAI, this is an acceptable approximation. A significant share of revenue comes from auto-renewing subscriptions and API usage, where consumption usually grows, so the current run rate is stable enough to use as a proxy for future annual revenue.

At the time of their latest rounds, OpenAI was valued at a notable premium to Anthropic, meaning it was more expensive on a per-dollar-of-revenue basis, even though it showed more modest results. This premium is largely historical. OpenAI was first to market with neural networks and had accumulated a significant portion of its valuation before Anthropic began growing faster.

The expected valuations discussed by FT bring the picture into line. The market values both companies at roughly 30 times annual revenue, and OpenAI’s historical premium disappears. In addition, by the time of the IPO and a new round, both will have increased ARR, and the multiples will compress further.

For comparison, here are the multiples of major tech IPOs in past years:

• Facebook — about 26x ARR
• Amazon — about 27.8x revenue for the 12 months before the listing
• Palantir — about 30x
• SpaceX — 103x

The calculation methods behind these benchmarks differ, so the comparison is approximate. But it does support the conclusion: in absolute terms, Anthropic and OpenAI will become among the most expensive companies ever to go public, while in terms of multiples there is nothing anomalous in these figures.

Revenue structure

The companies earn money from different customers:

• Anthropic — about 80% of revenue comes from API, while Claude Code adds another $2.5 billion, leaving about 20% from subscriptions.
• OpenAI — 26% of revenue comes from API and 16% from enterprise subscriptions at the Enterprise tier, meaning only 42% can confidently be classified as enterprise-related.

Some of OpenAI’s standard subscriptions are also used for work, but even with that adjustment, the business brings the company noticeably less money. From the outset, Anthropic targeted enterprise clients, and in large part it benefits from Claude’s availability on AWS — Amazon’s cloud platform, the world’s largest provider of computing power for business. Many companies already keep their infrastructure there, so Claude can be connected quickly and without unnecessary integrations.

Important caveat: these figures do not tell us which company has more users. Anthropic charges more for the same volume of tasks, so OpenAI may well lead in the number of clients and tasks solved even in the enterprise segment, simply monetizing it less effectively.

Compute commitments

The exact picture of debt usually has to be pieced together from fragments, since a significant share of infrastructure-related AI debt is currently off balance sheet. But internal financial documents have already leaked from both companies, clarifying the picture: for Anthropic, it is the IPO prospectus, and for OpenAI, the audited financial statements for 2025. Both documents disclose how much the companies committed to spend on compute.

These commitments come in two types. Some are locked in by binding contracts and will have to be paid regardless. Others are still intentions and framework agreements that can be revised.

• Anthropic — $518 billion, of which about 60%, or roughly $310 billion, falls under binding contracts.
• OpenAI — the total reaches $750 billion, of which about half, or roughly $375 billion, can be considered binding

OpenAI has already revised its plans. First, the company cut them from $1.4 trillion to $600 billion, and then raised them again. On binding contracts, the amounts are comparable. Historically, OpenAI has had more non-binding commitments, although recently the company has become more restrained.

Overall, Anthropic spends more cautiously on infrastructure. This reduces financial risk, but as we will see later, caution also has a price.

The path to profitability

Anthropic turned operating profitable for the first time in the second quarter of 2026 and told shareholders it expects to repeat the result in the third. For now, this refers to an adjusted figure, and the company does not disclose exact amounts. In the second quarter, revenue was $11.5 billion, three times higher than in 2025.

The leaked IPO prospectus provides a fuller picture for prior years. Anthropic’s operating loss by year:

• 2023 — $2 billion;
• 2024 — $8 billion;
• 2025 — $8 billion, if the net loss of $42 billion is adjusted to remove the $34 billion non-operating revaluation of financial liabilities.

In total, that comes to about $18 billion over three years. By comparison, according to OpenAI’s own leaked documents, its operating loss for 2025 alone was $20.9 billion on revenue of $13.07 billion, more than Anthropic accumulated over three years.

An important detail in how Anthropic arrived at these figures: over 2024–2025, its revenue grew 12-fold, while operating loss barely increased. This means the business is growing faster than the cost of serving it, and sooner or later it should turn profitable, which the second quarter of 2026 confirmed.

The companies also raised different amounts. Anthropic has raised a little over $130 billion, while OpenAI has raised about $190 billion. The larger cushion allows OpenAI to remain unprofitable for longer and invest more aggressively in infrastructure.

How the balance of power changed in 2026

Spring 2026 was Anthropic’s best period. Demand for Claude surged, Mythos and Fable were released, and by valuation the company overtook OpenAI and filed for an IPO. But then its own capacity suddenly became insufficient: Anthropic had to cut limits, raise token prices, and rent the Colossus data center from SpaceX — we wrote more about that deal here in our piece on SpaceX’s IPO.

In the summer, cheap Chinese models entered the market, and Kimi rose to third place in the Artificial Analysis rankings. Large companies began distributing tasks across different models to save money, and Claude’s high price became a vulnerability.

Meanwhile, OpenAI benefited from the capacity it had contracted in advance. When demand growth slowed, the company redirected that capacity to training new models and now releases them almost simultaneously with Anthropic, sometimes within a few hours. In the Intelligence Index from Artificial Analysis, Claude models still slightly outperform competitors, but OpenAI is ahead on the cost of solving tasks.

Conclusions

In the spring, the market believed in two ideas. The first said that Anthropic had already won the race and its lead was almost impossible to close. The second predicted OpenAI’s imminent collapse. Neither proved true.

Anthropic’s leadership turned out to be less durable than it seemed. It was supported by enterprise clients and high token prices, but that same pricing became a vulnerability when cheap alternatives appeared, and the shortage of capacity forced the company to limit clients. OpenAI, meanwhile, used its excess capacity and accelerated model releases.

Anthropic has already postponed its IPO from October to November. According to media reports, the company wants to show investors third-quarter results before the listing begins, and the decision was made even before statements by a former Anthropic researcher intensified debate about the pace of AI development. But amid the race to release new models and the anxious mood around AI, further delays cannot be ruled out.

Claude still has a strong position in the enterprise segment, and Anthropic has smaller losses. But without solving the problem of token cost and usage efficiency, the company will struggle to maintain its advantage.

In movies, it is usually clear which hero is right. Here, the line is not so easy to draw — each of the companies has managed to be both Ford and Ferrari. The race is not over yet, and the coming months before the IPO could well change the leader again.